Closed safooray closed 7 years ago
BayesOpt always assume that the function is noisy. Also, it might imply that your model is not suitable for your problem and have to tune the parameters.
Note that BayesOpt can work with discrete spaces, but it's better/easier for continuous.
BayesOpt keeps trying the same point. Why does it do it when it already knows the outcome of that point? After a few iterations it forces one random sampling, but gets right back to the old point and gets stuck.